Journal of Manufacturing Science and Mechanical Engineering
Journal of Manufacturing Science and Mechanical Engineering (JMSME) is an international peer-reviewed, open access journal.
HISTORY OF EXPLORATION & PRODUCTION AND THE OIL COMPANIES
This paper provides a comprehensive historical analysis of the oil exploration and production industry, examining its evolution through the intertwined lenses of corporate strategy, geopolitical conflict, and technological innovation. It argues that the sector's development has been a powerful force in shaping the modern global economy and international relations, while simultaneously being profoundly shaped by external political, economic, and environmental pressures. The study employs a dual-case framework for in-depth illustration: the corporate history of BP serves to trace the strategic adaptations and challenges of a major international oil company, from its imperial origins to its contemporary engagement with the energy transition. Concurrently, the Rumaila oil field in Iraq is analyzed as a microcosm of the industry's technical, operational, and geopolitical dimensions, highlighting its enduring significance and modernization. The analysis spans key historical phases, including the formative early discoveries, the rise of OPEC and the use of oil as a geopolitical weapon, and the persistent link between hydrocarbon resources and regional conflicts. It then investigates the contemporary pressures compelling transformation, particularly the dual imperatives of technological efficiency and climate responsibility. The discussion projects into the future of upstream operations, evaluating how digital technologies like artificial intelligence are revolutionizing exploration and production, and how climate-responsive strategies—including carbon management and investments in cleaner energies—are redefining corporate missions. Ultimately, this paper presents the oil industry not as a static entity, but as a dynamic and adaptive sector navigating an irreversible shift toward a lower-carbon global energy system.
Copyright (c) 2025 ZhiHao Zhu https://creativecommons.org/licenses/by/4.0
COMPOSITE OVER-WRAPPED PRESSURE VESSEL TECHNOLOGY FOR SPACECRAFT PROPULSION SYSTEMS
This paper systematically reviews global progress in composite overwrapped pressure vessels (COPVs) for space applications and projects their trajectory, synthesizing key advances from the United States, Europe and leading Asian nations in structural and reliability design, stress-fracture and low-cycle-fatigue life prediction, material selection, forming, qualification and non-destructive testing, including high-strength fibers, ultra-thin metallic liners, inheritable design principles and validated failure models, and summarizing representative work by principal Chinese institutes and universities; on this basis it proposes future Chinese directions-high-strength fiber optimization, advanced liner alloys, burst-factor and performance-factor tuning, next-generation NDT, upstream pre-research and Standardization-to underpin independent R&D and technological upgrading of high-performance aerospace COPVs.
Copyright (c) 2025 Bin Yu; TianJu Ma; Yun Zhang; Cheng Huang; SenDong Gu; HaiYan Li; LinFeng Chen https://creativecommons.org/licenses/by/4.0
STUDY ON THE PERFORMANCE OF STEEL STRUCTURE OF WAVY SUPER-LONG CENTRAL CORRIDOR
Based on the structural design and analysis of the Hangzhou Convention and Exhibition Center project, this paper focuses on the self-vibration characteristics, buckling performance and seismic resistance of the central corridor steel structure. The numerical simulation of the overall structure and key nodes was carried out by finite element software to verify the rationality and safety of its design. The research results show that the wave-shaped steel structure has good structural performance while improving the architectural aesthetics, and meets the seismic performance requirements under moderate and large earthquakes. The research in this paper provides a theoretical basis and technical reference for the design of steel structures similar to large convention and exhibition centers.
Hangzhou convention and exhibition center
Copyright (c) 2024 Yi Zhu; ZhiYuan Zhang; ZhiCheng Bai; ShenShen Zhu; ZhiBo Zhang https://creativecommons.org/licenses/by/4.0
THE ROLE OF ARTIFICIAL INTELLIGENCE IN ADVANCING BATTERY MANUFACTURING: A COMPREHENSIVE ANALYSIS
The integration of artificial intelligence into battery manufacturing represents one of the most significant technological advances in energy storage production of the past decade. This comprehensive study examines how AI is fundamentally transforming manufacturing processes, quality control, and materials innovation across the global battery industry. Through extensive analysis of implementation data from 150 manufacturing facilities spanning North America, Europe, and Asia, we demonstrate that AI integration has revolutionized production efficiency and quality control, leading to unprecedented improvements in manufacturing outcomes. Our findings, drawn from five years of operational data covering more than 500 million battery cells produced under AI-supervised conditions, reveal average productivity improvements of 35% and defect reduction rates of 45%. These results suggest that AI implementation is not merely an optimization tool but rather a fundamental paradigm shift in how advanced energy storage solutions are developed and manufactured.
Copyright (c) 2024 Anna Kowalski; Raj Patel https://creativecommons.org/licenses/by/4.0
A DEEP LEARNING APPROACH TO LITHOGRAPHIC HOTSPOT DETECTION IN SEMICONDUCTOR MANUFACTURING
This paper presents a novel deep learning approach to lithographic hotspot detection in semiconductor manufacturing, addressing the critical challenges posed by increasingly complex integrated circuit designs. As the demand for smaller, faster, and more efficient semiconductor devices continues to rise, the intricacies of the lithography process become more pronounced, leading to potential defects that can significantly impact yield and performance. Traditional hotspot detection methods, which primarily rely on rule-based and statistical techniques, often fall short in capturing the complexities of modern IC layouts, resulting in missed hotspots and compromised product quality. In contrast, this research leverages advanced machine learning techniques, specifically convolutional neural networks, to enhance the accuracy and reliability of hotspot detection. By training the model on both simulated and real-world datasets, the proposed framework demonstrates superior performance in identifying hotspots while minimizing false positives. The findings highlight the advantages of deep learning over conventional methods, showcasing its ability to learn intricate patterns and relationships within design data. This research not only contributes to the advancement of hotspot detection methodologies but also lays the groundwork for future applications of deep learning in various areas of semiconductor manufacturing. The implications of this study are far-reaching, as improved hotspot detection can lead to higher yields, better-performing devices, and ultimately, a more efficient semiconductor manufacturing process.
Copyright (c) 2024 Lily Zhang; Kenneth Wong https://creativecommons.org/licenses/by/4.0
INNOVATIVE TECHNOLOGIES AND METHODOLOGIES IN MANUFACTURING SCIENCES: ENHANCING PRODUCTIVITY, EFFICIENCY, AND SUSTAINABILITY THROUGH INTERDISCIPLINARY COLLABORATION
This document delves into the critical aspects of manufacturing sciences and mechanical engineering, emphasizing the integration of innovative technologies and methodologies. The primary purpose is to explore how advancements in these fields can enhance productivity, efficiency, and sustainability within the manufacturing sector. Through a comprehensive review of current literature and case studies, the document outlines various methods employed in modern manufacturing processes, including automation, additive manufacturing, and advanced materials engineering. Results indicate that the adoption of these advanced techniques not only optimizes production but also significantly reduces waste and energy consumption. Furthermore, the findings suggest that interdisciplinary collaboration among engineers, designers, and industry stakeholders is essential for driving innovation and tackling contemporary challenges. The document concludes by highlighting the importance of continuous research and development in manufacturing sciences, advocating for educational initiatives that bridge theoretical knowledge and practical application. By fostering a culture of innovation and embracing new technologies, the manufacturing industry can position itself for future growth and competitiveness in the global market.
Copyright (c) 2025 Okechukwu Chidoluo Vitus https://creativecommons.org/licenses/by/4.0
AIRCRAFT WING DESIGN THROUGH INTEGRATION OF OPENVSP AND ANSYS
To address the challenge of balancing modeling efficiency and computational accuracy in traditional wing design, this paper proposes a collaborative optimization method based on OpenVSP parametric modeling and high-fidelity CFD analysis using ANSYS. A parametric wing model is created in OpenVSP, and aerodynamic performance simulations are conducted in ANSYS Workbench. Case studies show that this method reduces the time for a single design iteration to 3.5 hours while maintaining lift coefficient errors below 8%, achieving a 68% improvement in efficiency compared to conventional processes.
Copyright (c) 2025 Wei Li https://creativecommons.org/licenses/by/4.0
REVIEW OF THE GUIDANCE SYSTEM OF AUTONOMOUS UNDERWATER VEHICLES IN CONFINED SEMI-STRUCTURED ENVIRONMENTS
This paper provides a review and summary of previous research on the guidance system of Autonomous Underwater Vehicles (AUVs). It introduces the guidance system, analyzes its elements, and offers detailed explanations of its submodules: Guidance, Navigation, and Control. The paper also points out the current research limitations, noting that while there are numerous studies on autonomous underwater vehicles, most focus solely on hardware or navigation issues, with limited exploration of the integrated design of the guidance system. Additionally, a brief overview of the components of the guidance system for autonomous underwater vehicles in confined semi-structured environments is presented.
Copyright (c) 2025 WeiWen Zhao https://creativecommons.org/licenses/by/4.0
A DATA-DRIVEN FRAMEWORK FOR INTELLIGENT COLD STORAGE MONITORING AND TEMPERATURE REGULATION
Cold storage systems are essential for ensuring the quality and safety of temperature-sensitive goods across industries such as food, pharmaceuticals, and biotechnology. However, traditional temperature regulation approaches often struggle with delayed fault detection, lack of adaptive response mechanisms, and inefficient energy consumption. As modern supply chains grow increasingly complex, the demand for intelligent, automated cold storage solutions has become more urgent. This paper proposes a comprehensive data-driven framework for intelligent cold storage monitoring and temperature regulation. By integrating Internet of Things (IoT) sensors, real-time data acquisition, machine learning (ML) algorithms, and predictive control models, the system continuously tracks environmental and equipment metrics. Anomaly detection techniques are used to identify deviations from normal behavior, while reinforcement learning is applied to optimize response strategies in varying operational contexts. The framework includes a cloud-based data processing layer, an ML-based anomaly detection engine, and a closed-loop control module capable of adjusting temperature settings proactively. Through simulations and real-world deployment scenarios, the system demonstrated improved temperature stability, faster fault diagnosis, and reduced energy consumption compared to conventional control mechanisms. The findings suggest that combining ML and IoT technologies provides a scalable and adaptive solution for next-generation cold storage management.
Copyright (c) 2025 Wei Zhang; Emily Hart https://creativecommons.org/licenses/by/4.0
HYBRID MODELING OF ELECTRIC VEHICLE BATTERY DEGRADATION USING PHYSICS-INFORMED MACHINE LEARNING
Accurate prediction of battery degradation is crucial for ensuring the reliability, safety, and performance of electric vehicles (EVs). While data-driven machine learning (ML) models offer high prediction accuracy, they often lack physical interpretability, limiting their application in critical systems. On the other hand, purely physics-based models provide deeper understanding but struggle to generalize across diverse operating conditions. This paper proposes a hybrid modeling approach that combines physics-informed machine learning (PIML) with empirical battery aging data to achieve both accuracy and interpretability. The model incorporates domain knowledge—such as electrochemical degradation mechanisms, capacity fade laws, and thermal effects—into a learning framework based on recurrent neural networks (RNNs) and gradient boosting. Experimental results on real-world EV battery datasets demonstrate that the hybrid model outperforms standalone physics-based and ML models in both prediction precision and consistency. This approach opens new avenues for predictive maintenance, extended battery lifespan, and optimized battery usage strategies.
Physics-Informed Machine Learning (PIML)
Copyright (c) 2025 Helena Schmidt; Jan Neumann https://creativecommons.org/licenses/by/4.0
MAINTENANCE AND MANAGEMENT OF LASER DIRECT WRITING LITHOGRAPHY MACHINE
The laser direct writing lithography machine is a key equipment for integrated circuits and semiconductor manufacturing. And it is a complex and highly precise device consisting of an optical system, mechanical system, electronic system, and computer system. The maintenance and management of the lithography machine directly affect the quality and stability of the lithography products, and ultimately influence the work efficiency of users and the competitiveness of enterprises. In response to the above issues, this paper proposes management and maintenance measures for laser direct writing lithography machines and related equipment, which is helpful to improve the usage and maintenance capabilities of users and manufacturers, reduce equipment operation costs, and provide useful references for the maintenance and management of precision equipment.
Copyright (c) 2025 FeiTong Luo https://creativecommons.org/licenses/by/4.0
APPLICATION OF ACCELERATED LIFE TESTING IN SOLDER JOINT LIFE PREDICTION
Accelerated life testing (ALT) is an efficient reliability evaluation method with significant application value in solder joint life prediction for electronic packaging. This paper systematically reviews the theoretical basis and practical applications of ALT in solder joint life prediction. It analyzes the main failure mechanisms such as thermomechanical fatigue, electromigration, and creep, discusses the principles and applicability of accelerated models such as Arrhenius, Coffin-Manson, and Norris-Landzberg, and elaborates on the calculation methods of acceleration factors and test design optimization considering stress types such as temperature, vibration, and humidity. Literature case studies show that ALT, by simulating long-term service conditions, can rapidly reveal the microstructural degradation characteristics of solder joints, significantly shortening the test cycle and improving prediction accuracy. The study further points out that combining data-driven methods with multi-physics coupling models is a promising future direction, effectively addressing challenges arising from multiple variable interactions and complex environments, and providing a scientific basis for the design of highly reliable electronic products.
Copyright (c) 2025 ZiQin Huang https://creativecommons.org/licenses/by/4.0
DEEP LEARNING-BASED FAULT DIAGNOSIS AND INTELLIGENT OPERATION OF CENTRIFUGAL PUMPS: MODELS, CHALLENGES, AND PERSPECTIVES
As one of the most critical power devices in industrial systems, the operational status of centrifugal pumps directly affects system safety, reliability, and economic efficiency. To address the limitations of traditional diagnostic methods—such as reliance on manual feature extraction and poor generalization—this paper provides a comprehensive review of recent advances in deep learning-based fault diagnosis and intelligent operation and maintenance (O&M) of centrifugal pumps. It first outlines the theoretical foundations and representative deep learning models, including convolutional neural networks (CNN), recurrent neural networks (RNN/LSTM/GRU), residual networks (ResNet), graph neural networks (GCN), and Transformers, and discusses their applications in cross-condition diagnosis, remaining useful life (RUL) prediction, and intelligent O&M. Furthermore, it summarizes the progress in key enabling technologies such as multi-sensor data fusion, transfer learning, self-supervised and meta-learning, physics-informed feature alignment, and digital twins, which significantly enhance diagnostic accuracy, robustness, and generalization. Studies indicate that deep learning-based approaches outperform traditional methods in automatic feature extraction, domain adaptation, and decision optimization, thus enabling the shift from passive monitoring to proactive maintenance. Nevertheless, challenges remain regarding data scarcity and labeling difficulty, limited model interpretability and generalization, and real-time computational constraints. Future research directions include: developing few-shot and self-supervised learning to alleviate data dependency; integrating physical knowledge with deep learning to improve interpretability and trustworthiness; designing lightweight models suitable for edge deployment; and advancing digital twin-driven lifecycle management and predictive maintenance. This review provides a systematic reference and future outlook for research and industrial applications of intelligent fault diagnosis and maintenance of centrifugal pumps.
Copyright (c) 2025 Fan Zhang; XiuLi Wang https://creativecommons.org/licenses/by/4.0
ANALYSIS OF MEASUREMENT TECHNOLOGY AND ITS EVOLUTION IN SURVEYING AND MAPPING ENGINEERING
Surveying and mapping engineering measurement technology is the direct application of surveying and mapping technology in the process of social construction and development. The application scope of traditional surveying and mapping engineering measurement technology is relatively narrow, limited to the fields of water conservancy, construction and transportation, and its main content is as follows Two aspects: mapping and setting out. With the continuous development of surveying and mapping engineering measurement technology, its application fields are becoming more and more extensive. At present, the relatively mature and widely used surveying and mapping engineering measurement technologies mainly include global positioning technology, remote sensing technology and geographical information system technology. The advantages of these three methods are relatively obvious, and in the actual application process, the accuracy of measurement work will be greatly improved. and efficiency, effectively saving the cost investment in surveying and mapping work, and playing a huge role in promoting the development of the surveying and mapping industry.
Copyright (c) 2024 Smita Haider https://creativecommons.org/licenses/by/4.0
ANALYSIS OF APPLICATION AND DEVELOPMENT TRENDS OF AUTOMATED INSTRUMENT CONTROL SYSTEMS
With the development of modern science and technology, artificial intelligence has penetrated into various existing industries in China. It not only effectively improves the work efficiency of the industry, but also brings It has stimulated the upgrading of software and hardware equipment in the entire industry. This article analyzes the application advantages of instrument automation control systems and combines its current development and application status. Based on the development trend of automated instrument control systems in the future, and based on the current development status of enterprises in China. corresponding suggestions for the development of instrument automation are put forward to realize the production and operation of petrochemical enterprises. Networked, model-based and scientific production management, and safe digitalization integrating scientific management and control.
Copyright (c) 2023 Hoang M. Canh https://creativecommons.org/licenses/by/4.0
MECHANICAL PROCESSING TECHNOLOGY OF ENGINEERING CERAMICS
Engineering ceramics have many excellent properties such as high hardness, good wear resistance, and stable performance, so they have been widely used in various industries. Based on relevant research by domestic and foreign scholars, new methods of engineering ceramic processing technology have made great progress. Due to the significant hard and brittle characteristics of engineering ceramics, mechanical processing is the most commonly used traditional processing technology. Combining relevant literature and data in recent years, this article explains the successive development of engineering ceramics machining technologies at home and abroad such as high-speed/ultra-high-speed grinding, deep-cut creep-feed grinding, and high-speed deep grinding. In addition, two new processing technologies based on edge fragmentation effect, cutting-push processing and energy-assisted cutting processing, are also explained.
Copyright (c) 2024 Todd Magleby https://creativecommons.org/licenses/by/4.0
APPLICATION OF HIGH-VOLTAGE DC POWER SUPPLY IN DATA CENTER COMPUTER ROOM
This article mainly discusses the development background of high-voltage DC power supplies, introduces the origin of high-voltage DC power supply products, the development schools of foreign high-voltage DC power supplies, and the domestic high-voltage DC power supplies of 240V represented by China Telecom and 336V represented by China Mobile. 2 major series in the industry. It also discusses the advantages and disadvantages of high-voltage DC power supplies compared to UPS uninterruptible power supplies in the construction of data center computer rooms, and predicts the future application methods of high-voltage DC power supplies in data center computer rooms. Finally, a data center high-voltage DC power distribution design case is used as a reference for readers to understand high-voltage DC power supplies and their working applications.
Copyright (c) 2024 Steven Elwany https://creativecommons.org/licenses/by/4.0
PROGRESS IN COPPER ALLOY ADDITIVE MANUFACTURING TECHNOLOGY
The rapid development of additive manufacturing technology has provided new development impetus for copper alloy manufacturing technology. This article mainly summarizes the methods of different copper alloy additive manufacturing processes at home and abroad in recent years, analyzes the problems encountered in the additive manufacturing research process such as the easy grain size of additive manufacturing samples, the easy formation of cracks, and the easy introduction of impurities, and compares them. Microstructure and mechanical properties of copper alloy samples prepared under different additive manufacturing processes. On this basis, this paper focuses on the progress of copper alloy additive manufacturing technology research in different additive manufacturing process methods, and compares the microstructure and mechanical properties of additive manufacturing samples and traditional casting samples. Finally, the research progress of copper alloy additive manufacturing technology is summarized, and its development prospects and development directions are prospected.
Copyright (c) 2024 Coe C. Leu https://creativecommons.org/licenses/by/4.0
EQUIPMENT SYSTEM SUPPORTABILITY ANALYSIS
Following the idea of "system - system construction - system supportability", the system concept and its construction mechanism are analyzed in depth, and the concept of system supportability is defined; the current status of equipment system supportability research at home and abroad is analyzed, focusing on support A classified review was conducted on the research on task planning and scheduling, support resource demand determination and optimal allocation, and maintenance implementation and optimization. The research status of the two aspects of "index construction-intelligent decision-making" that address key needs in system supportability research was analyzed, pointed out the characteristics of the current research, and proposed possible technical solutions for the next step. It has certain guiding significance for subsequent research on equipment system supportability.
Copyright (c) 2024 Ali Amini https://creativecommons.org/licenses/by/4.0
OPTIMIZATION MEASURES OF AUTOMATED CONTROL IN CHEMICAL PRODUCTION SAFETY
Electronic technology has advanced significantly, leading to the widespread application of automation across multiple industries. This integration has resulted in a substantial liberation of the workforce, enhancing both operational efficiency and financial profitability for enterprises. However, the chemical industry poses inherent dangers, necessitating careful consideration of the associated risks when introducing automated control systems. To ensure the effective and safe utilization of automation in chemical production, it is imperative to establish clear operational guidelines and safety measures.
Copyright (c) 2024 Nima Eslami https://creativecommons.org/licenses/by/4.0
PREDICTIVE MAINTENANCE USING ML TO OPTIMIZE PLANT EFFICIENCY AND REDUCE EMISSIONS
In the modern industrial landscape, the integration of predictive maintenance (PdM) using machine learning (ML) has become essential for optimizing plant efficiency and minimizing emissions. This paper explores the transformative potential of predictive maintenance, which leverages data-driven insights to anticipate equipment failures and facilitate timely interventions. By transitioning from traditional maintenance strategies—reactive and preventive—to a proactive approach, organizations can significantly reduce unplanned downtime and enhance operational performance. The study reviews the historical development of predictive maintenance methodologies, highlights current trends in ML applications, and presents case studies demonstrating successful implementations across various industries. The findings reveal that predictive maintenance not only improves equipment reliability and operational efficiency but also contributes to substantial reductions in emissions, thereby promoting sustainable industrial practices. A comprehensive framework for implementing predictive maintenance using machine learning techniques is proposed, emphasizing the importance of data collection, preprocessing, and model development. The paper concludes with a call to action for industries to adopt predictive maintenance solutions, fostering collaboration between academia and industry for future advancements.
Copyright (c) 2024 Seolhwa Park; Lindsay Berry; ChanJun Lim https://creativecommons.org/licenses/by/4.0
RESEARCH ON THE APPLICATION OF INTELLIGENT CONTROL SYSTEM IN URBAN LANDSCAPE LIGHTING
This article studies the application of intelligent control systems in urban landscape lighting. With the further integration of Internet technology and LED chip technology, urban landscape lighting has entered the era of intelligence. Traditional switching control methods can no longer meet the needs of modern urban landscape lighting, and the development of intelligent control systems provides a new solution for urban landscape lighting. This article analyzes the advantages and application cases of intelligent control systems in urban landscape lighting, and explores the future development trends of intelligent control systems. Intelligent control systems can achieve remote control, real-time monitoring, and data analysis and other functions, providing more refined management methods for urban management departments. In the future, with the continuous advancement of technology and the continuous expansion of application scenarios, intelligent control systems will play a more important role in urban landscape lighting.
Copyright (c) 2024 Yao Shi; RenFei Qian; ShengWei Zhou; DaiQuan Chao https://creativecommons.org/licenses/by/4.0
ADVANCEMENTS IN THE DEVELOPMENT OF ELECTRO-HYDRAULIC COMPOSITE BRAKING SYSTEMS FOR ELECTRIC VEHICLES
This paper meticulously categorizes, hones, and summarizes pertinent technical matterspertinent technical matters both domestically and internationally, focusing on the optimal design, system control, and testing platform of the electro-hydraulic composite braking system. It also presents a comprehensive review of the advancement of electro-hydraulic composite braking systems for electric vehicles, offering a future perspective. Research indicates that the integration, reliability, and robustness of electro-hydraulic composite braking systems are crucial areas for further improvement, as they emerge as a significant development trajectory for braking systems in electric vehicles.
Copyright (c) 2024 Zoja Aksjonov https://creativecommons.org/licenses/by/4.0
HIGH-PRECISION CONSTRUCTION TECHNOLOGY FOR LARGE-AREA SANDWICH-TYPE LIGHTWEIGHT AND HEAVY-LOAD FLOORING
In view of the shortcomings of traditional large-area floors in terms of bearing capacity, deadweight, cost and crack control, this paper proposes a sandwich-type lightweight and heavy-load flooring construction technology. This technology combines solid waste slag concrete cushion layer, film sliding layer, steel fiber concrete and diamond wear-resistant surface layer to ensure that the bearing capacity reaches 5 t/m2, effectively solving the problems of high bearing capacity, heavy deadweight and crack prevention. At the same time, the structure saves costs, improves the utilization of solid waste materials, meets the requirements of green buildings, and provides an important reference for the construction of lightweight and heavy-load wear-resistant floors in China.
Copyright (c) 2024 Yi Zhu; XiaoXia Zhao; ZhiCheng Bai; ZhiYuan Zhang; Lei Wu; XuanZhong Luo https://creativecommons.org/licenses/by/4.0
STABILITY AND UNLOADING CALCULATION ANALYSIS OF TEMPORARY SUPPORT FRAME OF RING-LAYERED HOLIER-WEB TRUSS
This paper takes the Beijing-Hangzhou Grand Canal Museum project in China as the background, introduces the stress characteristics of the ring-layered holier-web truss of the project, and designs a temporary support frame structure based on its stress characteristics to ensure the safe construction of the project. Yingjianke software is used to verify the overall stability and floor shear bearing capacity of the temporary support frame, and the support frame during the construction process is subjected to stress analysis. In addition, the active control method is used for unloading to realize the conversion of the force system, and the stress and strain measurement points are arranged in the key sections to monitor the stress and strain in real time during the structure construction and unloading process. The construction method of this project can provide a technical reference for the construction of similar projects.
Copyright (c) 2024 JiaLi Cao; XunYin Liu; BaoAn Zhang; JiangLong Meng; ZhiYuan Zhang; XiaoXia Zhao https://creativecommons.org/licenses/by/4.0
ENERGY CONSUMPTION IN MANUFACTURING SYSTEMS
Green manufacturing represents a paradigm shift towards sustainable production processes that minimize environmental impact by reducing energy consumption and conserving natural resources. This paper explores green manufacturing strategies, focusing on the adoption of energy-efficient technologies, the use of recycled materials, and the redesign of manufacturing processes to minimize waste and emissions. The research highlights the importance of energy reduction at multiple system levels—process, equipment, facility, and supply chain—demonstrating how dynamic scheduling and modern technologies can lead to significant energy savings. The study emphasizes the growing need for industries to adopt green manufacturing practices as a response to global warming and environmental degradation, while also recognizing the financial benefits of reduced energy consumption. The integration of environmentally friendly designs, sustainable materials, and optimized energy usage throughout the manufacturing process is presented as crucial to achieving both economic and environmental sustainability in the manufacturing sector.
Copyright (c) 2024 Ogbeide S. O. https://creativecommons.org/licenses/by/4.0
INVESTIGATE THE PERFORMANCE OF NONLINEAR BIPOLAR TRANSISTOR AT HIGH TEMPERATURE
An increase in the board temperature can have an effect on the basic characteristics of electronic elements which may influence the performance of the circuit. The objective of this paper is to investigate the influence of thermal rise on some characteristics of Bipolar junction transistor. Some static and dynamic characteristics have been experimentally measured and analyzed of a transistor type 2SC2120 at high temperatures. The obtained results indicate that with an increase in temperature over the range 30-90 °C, a collector current will increase by about 0.04 A, whereas the current will be around 0.12 A. The applied threshold voltage has been droped from 0.63 V to 0.45 V. The obtained results also illustrate that the reverse breakdown of emitter-to-base transition capacitance has been increased from 41 pF to 47 pF.
Copyright (c) 2024 Ghanim Thiab Hasan; Ali Hlal Mutlaq; Nabeel Akram Mohamed Ali https://creativecommons.org/licenses/by/4.0
RESEARCH PROGRESS OF THREE-DIMENSIONAL LASER SCANNING TECHNOLOGY IN SOIL AND WATER CONSERVATION AND DESERTIFICATION PREVENTION
Three-dimensional laser scanning technology is a new method that has emerged in recent years for soil erosion monitoring, wind-sand landforms, and effectiveness evaluation of sand prevention measures. Soil and water conservation research and desertification prevention and control play an important role in promoting. This article reviews the previous use of three-dimensional laser scanning technology in soil and water conservation and desertification prevention and control work. The application in the work is summarized, and the current problems and follow-up research are discussed, with a view to providing suggestions for the further development and application of 3D laser scanning technology.
Copyright (c) 2023 Julio L. Michalek https://creativecommons.org/licenses/by/4.0
CURRENT STATUS AND DEVELOPMENT OF COAL MINE GROUND PRODUCTION SYSTEM AUTOMATION TECHNOLOGY
The composition of the coal mine ground production control system is relatively complex., includes computer software, Telecommunication, computer integrated management and control by and mechatronics and many other technologies. A brief description of the coal mine area surface production Current status and problems of system automation technology, and explore the ground production system traditional development strategy, Hope this provides some guidance and help.
Copyright (c) 2023 Karl R. Kumar https://creativecommons.org/licenses/by/4.0
APPLICATION AND DEVELOPMENT OF MECHANICAL AUTOMATION TECHNOLOGY IN MACHINERY MANUFACTURING INDUSTRY
Processing and producing products in an automated and continuous manner is the main feature of mechanical automation. This article uses mechanical automation technology in machinery The application in manufacturing industry is the theme of discussion. The concept and development situation of mechanical automation technology are analyzed, and the mechanical automation technology is elaborated from three aspects: integration, intelligence and flexibility. Specific applications of automation technology in the manufacturing industry.
Copyright (c) 2024 Jyoti Donmez https://creativecommons.org/licenses/by/4.0